package ds_industry_2025.ds.ds_02.T2

import org.apache.hudi.DataSourceWriteOptions._
import org.apache.hudi.QuickstartUtils.getQuickstartWriteConfigs
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.expressions.Window
import org.apache.spark.sql.functions._

import java.text.SimpleDateFormat
import java.util.{Calendar, Properties}

/*
 5、将ods_ds_hudi库中order_info表昨天的分区（子任务一生成的分区）数据抽取到dwd_ds_hudi库中fact_order_info的动态分区表，分
 区字段为etl_date，类型为String，取create_time值并将格式转换为yyyyMMdd，同时若operate_time为空，则用create_time填充，
 并添加dwd_insert_user、dwd_insert_time、dwd_modify_user、dwd_modify_time四列，其中dwd_insert_user、dwd_modify_user
 均填写“user1”，dwd_insert_time、dwd_modify_time均填写当前操作时间，并进行数据类型转换。id作为primaryKey，operate_time作
 为preCombineField。使用spark-shell执行show partitions dwd.fact_order_info命令，将结果截图粘贴至客户端桌面【Release\任
 务B提交结果.docx】中对应的任务序号下；
*/
object t5 {

  def main(args: Array[String]): Unit = {
    val spark = SparkSession.builder()
      .master("local[*]")
      .appName("t1")
      .config("hive.exec.dynamic.partition.mode", "nonstrict")
      .config("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
      .config("spark.sql.extensions", "org.apache.spark.sql.hudi.HoodieSparkSessionExtension")
      .enableHiveSupport()
      .getOrCreate()

    val conn = new Properties()
    conn.setProperty("user", "root")
    conn.setProperty("password", "123456")
    conn.setProperty("driver", "com.mysql.jdbc.Driver")

    val day = Calendar.getInstance()
    val current_time = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(day.getTime)
    day.add(Calendar.DATE, -1)
    val yesterday = new SimpleDateFormat("yyyyMMdd").format(day.getTime)

    val ods_path = "hdfs://192.168.40.110:9000/user/hive/warehouse/ods_ds_hudi.db/order_info"
    val dwd_path="hdfs://192.168.40.110:9000/user/hive/warehouse/dwd_ds_hudi.db/fact_order_info"

    spark.read.format("hudi").load(ods_path)
      .drop("etl_date")
      .withColumn("operate_time",
        when(col("operate_time").isNull,col("create_time")).otherwise(col("operate_time")))
      .withColumn("dwd_insert_user", lit("user1"))
      .withColumn("dwd_insert_time", to_timestamp(lit(current_time)))
      .withColumn("dwd_modify_user", lit("user1"))
      .withColumn("dwd_modify_time", to_timestamp(lit(current_time)))
      .withColumn("etl_date",date_format(col("create_time"),"yyyyMMdd"))
      .write.format("hudi").mode("append")
      .options(getQuickstartWriteConfigs)
      .option(RECORDKEY_FIELD.key(), "id")
      .option(PRECOMBINE_FIELD.key(), "operate_time")
      .option(PARTITIONPATH_FIELD.key(), "etl_date")
      .option("hoodie.table.name", "fact_order_info")
      .save(dwd_path)


    //  spark.sql("select count(*) from dwd_ds_hudi.dim_province where etl_date=(select max(etl_date) from dwd_ds_hudi.dim_province)").show

    spark.close()
  }

}
